Assessment of atmospheric correction methods in MSI imagery for deriving bathymetry and substrates of shallow-water coral reefs by Wei Huang, Wei Huang, Wei Huang, Wei Huang, Jun Zhao, Mingjie Li, Mingjie Li, Mingjie Li, Quansheng Lou, Quansheng Lou, Nanyang Yan, Nanyang Yan, Nanyang Yan, Shaojie Sun

“…These include short-wave infrared band Glint Correction (GC), DeGlint (DG), and near-infrared band intercept (DG865) algorithms to enhance glint correction after the DSF processor. …”
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MSF-GhostNet: Computationally Efficient YOLO for Detecting Drones in Low-Light Conditions by Maham Misbah, Misha Urooj Khan, Zeeshan Kaleem, Ali Muqaibel, Muhamad Zeshan Alam, Ran Liu, Chau Yuen

“…The proposed solution also outperformed several other state-of-the-art algorithms exists in the literature.…”
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Effect of phosphorus fractions on benthic chlorophyll-a: Insight from the machine learning models by Yuting Wang, Sangar Khan, Zongwei Lin, Xinxin Qi, Kamel M. Eltohamy, Collins Oduro, Chao Gao, Paul J. Milham, Naicheng Wu

“…To address this gap, we applied two machine learning algorithms—random forest (RF), and artificial neural networks (ANN) to predict benthic chl-a concentrations by incorporating these specific P fractions as separate variables. …”
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Pan-Cancer Analysis of Disulfidptosis-Related Genes Affecting Prognosis and Tumor Microenvironment by Jingyang SUN, Rongxuan JIANG, Liren HOU, Huanhuan DONG, Yihan LIN, Niuniu DONG, Guangjian ZHANG, Yanpeng ZHANG

“…MethodsPan-cancer RNA-seq data, mutation profiles, clinical information, TMB, MSI, stemness scores, and tumor and immune microenvironment data contained in TCGA and various open-source online databases, and multi-group R-language algorithms were used for comprehensive analysis. The expression levels of DRGs at the cellular level were experimentally validated using qPCR. …”
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Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases by Yuji Miyamoto, Takeshi Nakaura, Mayuko Ohuchi, Katsuhiro Ogawa, Rikako Kato, Yuto Maeda, Kojiro Eto, Masaaki Iwatsuki, Yoshifumi Baba, Toshinori Hirai, Hideo Baba

“…Employing Random Forest and Boruta algorithms, we identified significant features for responder-non-responder differentiation. …”
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Identification and quantification of transposable element transcripts using Long-Read RNA-seq in Drosophila germline tissues by Rebollo, Rita, Gerenton, Pierre, Cumunel, Eric, Mary, Arnaud, Sabot, François, Burlet, Nelly, Gillet, Benjamin, Hughes, Sandrine, S. Oliveira, Daniel, Goubert, Clément, Fablet, Marie, Vieira, Cristina, Lacroix, Vincent

“…Methods to identify and quantify TE transcription have mostly relied on short RNA-seq reads to estimate TE expression at the family level while using specific algorithms to discriminate copy-specific transcription. …”
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On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study by Ardit Dvorani, Constantin Wiesener, Christina Salchow-Hommen, Magdalena Jochner, Lotta Spieker, Matej Skrobot, Hanno Voigt, Andrea Kuhn, Nikolaus Wenger, Thomas Schauer

“…<italic>Methods:</italic> We present a new technical solution, that runs detection and cueing algorithms directly on the sensing and cueing devices, bypassing the smartphone. …”
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Preoxygenation in difficult airway management: high-flow oxygenation by nasal cannula versus face mask (the PREOPTIDAM study). Protocol for a single-centre randomised study by Samir Jaber, Karim Asehnoune, Fanny Feuillet, Mickael Vourc’h, Donatien Huard, Gabrielle Baud, Arthur Guichoux, Marielle Surbled, Melanie Tissot, Anne Chiffoleau, Christophe Guitton

“…Introduction Although preoxygenation and airway management respond to precise algorithms, difficult intubation (DI) remains a daily challenge in intensive care units and in the operating rooms because of its frequent complications, including hypoxaemia. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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The multiple uses of artificial intelligence in exercise programs: a narrative review by Alberto Canzone, Alberto Canzone, Giacomo Belmonte, Antonino Patti, Domenico Savio Salvatore Vicari, Domenico Savio Salvatore Vicari, Fabio Rapisarda, Valerio Giustino, Patrik Drid, Antonino Bianco

“…BackgroundArtificial intelligence is based on algorithms that enable machines to perform tasks and activities that generally require human intelligence, and its use offers innovative solutions in various fields. …”
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Expert Consensus on the Management of Acute Otitis Media in India: A Delphi Study by Tanu Singhal, Shyam Kukreja, Jaydeep Choudhury, Vijay Yewale, Balasubramanian Sundaram, Jagdish Chinnappa, Suhas Prabhu, Balaji Veeraraghavan, Camilla Rodrigues, Vidya Krishna, Winsley Rose, Samir Bhargava

“…Finally, experts agreed to include 67 statements pertaining to risk factors, resistant strains, conservative and symptomatic management, and antibiotic treatment algorithms for AOM and OME. Conclusion: The consensus recommendations provide systematic guidance to clinicians on the appropriate management of AOM and OME. …”
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UNet-Att: a self-supervised denoising and recovery model for two-photon microscopic image by Yuer Lu, Yongfa Ying, Chen Lin, Yan Wang, Jun Jin, Xiaoming Jiang, Jianwei Shuai, Xiang Li, Jinjin Zhong

“…The UNet-Att model proves to surpass mainstream algorithms in the dual objectives of denoising and preserving the textural intricacies of original images, which is evidenced by an increase of 9.42 dB in the high Peak Signal-to-Noise Ratio (PSNR) coupled with an improvement of 0.1131 in the Structural Similarity Index Measurement (SSIM). …”
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Towards PErsonalised PRognosis for children with traumatic brain injury: the PEPR study protocol by Jaap Oosterlaan, Marsh Königs, Job B M van Woensel, Marc Engelen, Marjan E Steenweg, Petra J W Pouwels, Cece C Kooper, Hilgo Bruining, Arne Popma, Dennis R Buis, Maayke Hunfeld

“…In addition, the potential added value of advanced neuroimaging data and the use of machine learning algorithms in the development of prognostic models will be assessed.Methods and analysis 210 children aged 4–18 years diagnosed with mild-to-severe TBI will be prospectively recruited from a research network of Dutch hospitals. …”
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Adverse events in the nervous system associated with blinatumomab: a real-world study by Wen Gao, Jingwei Yu, Yifei Sun, Zheng Song, Xia Liu, Xue Han, Lanfan Li, Lihua Qiu, Shiyong Zhou, Zhengzi Qian, Xianhuo Wang, Huilai Zhang

“…The reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence interval progressive neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms were utilized for data mining. Results A total of 5,962 blinatumomab-related cases were analyzed. …”
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Development of robust machine learning models for predicting flexural strengths of fiber-reinforced polymeric composites by Abdulhammed K. Hamzat, Umar T. Salman, Md Shafinur Murad, Ozkan Altay, Ersin Bahceci, Eylem Asmatulu, Mete Bakir, Ramazan Asmatulu

“…This study investigates the potential of machine learning (ML) techniques to predict the flexural properties of fiber-reinforced composites accurately and efficiently. Five ML algorithms—Light gradient boosting regressor (LGBR), Extra tree regressor (ETR), Decision tree regressor (DTR), Histogram-based gradient boosting regressor (HGBR), and Adaptive boosting regressor (ABR)—were employed to predict the flexural strengths using both experimental data generated in-house and data collected from open literature. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…Decision tree, XGBoost, and random forest algorithms, respectively, were applied for the secondary prediction. …”
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Attention-enhanced optimized deep ensemble network for effective facial emotion recognition by Taimoor Khan, Muhammad Yasir, Chang Choi

“…In recent studies, various algorithms have encountered several challenges such as data scarcity, low-resolution images, and suboptimal performance, particularly in real-time applications. …”
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Novel genes involved in vascular dysfunction of the middle temporal gyrus in Alzheimer’s disease: transcriptomics combined with machine learning analysis by Meiling Wang, Aojie He, Yubing Kang, Zhaojun Wang, Yahui He, Kahleong Lim, Chengwu Zhang, Li Lu

“…Finally, combining bulk RNA sequencing data and two machine learning algorithms (least absolute shrinkage and selection operator and random forest), four characteristic Alzheimer’s disease feature genes were identified: somatostatin (SST), protein tyrosine phosphatase non-receptor type 3 (PTPN3), glutinase (GL3), and tropomyosin 3 (PTM3). …”
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A Comparative Study of Machine Learning Techniques for Predicting Mechanical Properties of Fused Deposition Modelling (FDM)-Based 3D-Printed Wood/PLA Biocomposite by Prashant Anerao, Atul Kulkarni, Yashwant Munde, Namrate Kharate

“…Four distinct machine learning algorithms have been selected for predictive modeling: Linear Regression, Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost). …”
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An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features by Junjie Wang, Lei Jiang, Le Zhang, Yaqi Liu, Qihong Yu, Yuheng Bu

“…This model integrates diverse algorithms and incorporates weather factors, while regionalizing characteristics of natural gas usage, thereby achieving accurate forecasts of natural gas purchase volumes. …”
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